Pediatric septic shock continues to be a major public health problem in the United States. The systemic inflammatory response syndrome (SIRS) is biologically linked to septic shock and reflects a generic inflammatory state present in many critically ill children. We are studying this clincial problem by establishing a national-level genomic data bank of children with SIRS and septic shock, and conducting of genome-wide scans through the application of microarray technology. Over the last 2.5 years we have found: a) the existence of clinically distinct subgroups of critically ill children with SIRS or septic shock having distinct gene expression profiles; b) the existence of major relevant gene networks within these subgroups of patients; c) differential expression of these networks between the patient subgroups; d) potential biomarkers for poor outcome (death) in pediatric septic shock; and e) the existence of one major gene network that is largely under expressed in non-survivors of pediatric septic shock. These findings have led to new hypotheses that are currently being taken back to the laboratory and bedside for validation. We now seek to build on the success of this program by continuing to build the data bank and conducting further microarray-based experiments. While we seek to continue discovery-oriented data mining with a larger data set, the main focus of the program will now be to address several prospectively designed questions. In Specific Aim 1 we will test the hypothesis that subgroups of patients with SIRS and septic shock exist by applying bioinformatic approaches that make use of a trainining data set and a validation data set. In Specific Aim 2 we will test the hypothesis that development (modeled by groups of children within specific age ranges) and pathogen- associated factors strongly influence the genome level expression profiles of children with SIRS and septic shock. In Specific Aim 3 we will test the hypothesis that the genome-level expression profiles of children with SIRS and septic shock can be more accurately defined by analyzing RNA from specific white blood cell subpopulations. The data generated through this program will serve to substantially enhance our genome level understaning of SIRS and septic shock and provide the foundation for novel hypotheses, diagnostic approaches, and therapies. [unreadable] [unreadable] [unreadable]